Operational Life Research Articles

Implementation of Fuzzy Logic Scheme for Assessment of Power Transformer Oil Deterioration Using Imprecise Information

This research aims to analyze the implementation of a fuzzy logic-based approach in improving the diagnosis of power transformer oil deterioration, which is critical for maintaining the efficient performance and operational life of transformers. Traditional diagnoses are based on strict measurements that do not account for the factors of variability and uncertainty of the actual data. In this article, we perform six different types of tests in this regard, and data have been collected during the period of 2021 to 2022 of 188 power transformer failures in the New KotLakhpat Lahore unit, whose voltage range is 132/66 kv and rating capacity is 40/50 MVA. In this case, a fuzzy logic-based scheme is developed based upon the membership function, a rule-based and defuzzification method that works with imprecision and the implementation of uncertainty in assessing the condition of transformer oils. Moisture, acidity, and a dissolved gas analysis indicator, along with other indication approaches such as interfacial tension, viscosity, and tangent delta measurement, are used to analyze the deterioration process in transformer oils. In the visual representation, oil samples with the following properties were first fuzzified: 19.9 mm2/s of viscosity, 0.453 mgKOH/g of acidity, 695 ppm of DGA, 20.8 mg/kg of moisture, 19.98 of IFT, and 4.35 × 100.14 of tangent delta. The output that was generated by software using the values entered into the parameters (HI and Age) after defuzzification is 45. Fuzzy logic serves as a concrete framework for transforming the diagnostics system and deterring the threats to the entire transformer’s health and reliability in the future. By using this technique, various faults were hypothetically and practically analyzed in a transformer to implement early detection technologies with the possibility to reduce maintenance costs and extend operational life up to 45 years. Various case studies indicate the effectiveness of fuzzy logic in comparison to traditional diagnostics.

Improving the operational life and reliability of the machine and tractor fleet by non-selective methods of tribotechnics

The fl eet of domestic tractors and combines has signifi cantly used up its operational life, has a reduced time to failure, frequent repairs and high operating costs: up to 50 billion rubles per year. The engineering service of agricultural enterprises has signifi cantly weakened, most of the maintenance work on domestic machines is carried out by the owners of the machinery themselves, which causes their low quality and frequent failures. In this regard, new methods and means are being developed to improve the reliability and service life of machines, which will also affect imported equipment.

Was the abolition of the Aboriginal and Torres Strait Islander Commission an act of dispossession?

AbstractThe Aboriginal and Torres Strait Islander Commission (ATSIC) has been described as one of the most comprehensive regional and national governance structures for Indigenous people in Australia. This paper looks briefly at its operational life between 1990 and 2005 and focusses on its abolition, arguing that this was an act of dispossession. The ATSIC was, for its time, a remarkable achievement for both the nation state and Indigenous people. Acting as an institution to both represent and deliver services to Indigenous people, the ATSIC model was, and could have remained, a powerful organisation for enacting critical change. Constructed and then removed by the nation state, the ATSIC's abolition dispossessed Indigenous people of a political framework dedicated to organising an Indigenous collective voice. This dispossession, different from earlier waves of dispossession from land, resources and cultural freedoms, can be understood by the application of critical Indigenous institutional analysis. Through its own structure and electoral representation, the ATSIC had made visible the quest for self‐determination and gave Indigenous people decision‐making powers not since replicated. Redirecting ATSIC's limited decision making back to government exposed the illusion of control. The ATSIC's abolition left a void in the growing capability of Indigenous people to self‐determine and a gaping hole in Australia's national political imagination.

Failure analysis of ternary lithium-ion batteries throughout the entire life cycling at high temperature

The operation life is a key factor affecting the cost and application of lithium-ion batteries. This article investigates the changes in discharge capacity, median voltage, and full charge DC internal resistance of the 25Ah ternary (LiNi0.5Mn0.3Co0.2O2/graphite) lithium-ion battery during full life cycles at 45 °C and 2000 cycles at 25 °C for comparison. The batteries before and after cycling were disassembled, and the structure, morphology, interface characteristics, element content of the cathode and anode plates of the battery were characterized. By analyzing the failure factors of the performance of the ternary batteries during the 45 °C cycling, a reaction mechanism for the rapid decline of high-temperature cycling performance of ternary batteries has been proposed. The results show that the performance degradation of the ternary lithium-ion batteries in the whole life operated at high temperature is characterized by slow decline in the initial stage and rapid drop in the latter stage. Further analysis of physical and chemical performance revealed irreversible damage to both the cathode and anode. The dissolution of transition metal ions from the cathode and their deposition on the anode surface catalyze the decomposition of electrolyte solvents to produce a large amount of gas. Gassing, accompanied by the deposition of Li2CO3 and the thickening of SEI, leads to an increase in the internal resistance of the battery. The coupling between gassing and increased internal resistance is responsible for the rapid drop in the performance of the ternary batteries during high-temperature cycling.

Performance of 3D trench silicon pixel sensors irradiated up to [formula omitted]

Tracking particles at extreme fluences requires the accurate measurement of the charged particle timing at the pixel level in order to cope with the increased occupancy of HL-LHC experiments. Maintaining this precision throughout the operational life of the detector is crucial. This work demonstrates that the 55×55μm2 wide 150μm thick 3D trench-type pixels, developed by the TimeSPOT Collaboration, maintain the performance of non-irradiated sensors even after exposure to fluences as high as 1⋅10171MeVneqcm−2. The preliminary results of a beam test characterization using minimum ionizing particles at the SPS North area beam facility reveal that the charge collection and the time resolution of the irradiated sensors are comparable to those of non-irradiated ones, by increasing the operational bias voltage. A minor reduction in detection efficiency, approximately 4%, is observed post-irradiation. Currently, 3D trench-type pixels are among the fastest pixel detectors available for tracking charged particles and hold significant promise for future tracking system upgrades. This preliminary evaluation suggests their suitability for use in even harsher radiation environments than High Luminosity Large Hadron Collider (HL-LHC) such as future experiments at the Future Circular Hadron Collider (FCC-hh).

Magneto-acousto-electrical tomography based on frequency response compensated linearly frequency-modulated signal stimulation

Objective. In magneto-acousto-electrical tomography (MAET), linearly frequency-modulated (LFM) signal stimulation uses much lower peak voltage than the spike pulse stimulation, lengthening the operation life of the transducer. However, due to the uneven frequency responses of the transducer, the low-noise amplifier (LNA), and the bandpass filter (BPF), MAET using LFM signal stimulation suffers from longitudinal resolution loss. In this paper, frequency response compensated linearly frequency-modulated (FRC-LFM) signal stimulation is investigated to resolve the problem.Approach. The physical model of measurement of the frequency responses of the transducer and the cascading module of the detection electrodes, the LNA, and the BPF is constructed. The frequency responses are approximated by fitting a curve to the measurement data. The frequency response compensation function is set to the reciprocal of the product of the frequency responses. The digital FRC-LFM signal is generated in MATLAB and converted to analog signal through an arbitrary waveform generator. Two groups of MAET experiments are designed to confirm the performance of the FRC-LFM signal stimulation. Pure agar phantom with rectangular through-holes and agar phantom with pork tissue inclusion serve as the samples.Main results. The pulse-compressed magneto-acousto-electrical signal obtained using FRC-LFM stimulation has narrower main-lobe than that obtained using LFM excitation, although the signal to noise pulse interference ratio of the former is little lower than that of the latter, which is due to the limitation of the power amplifier. FRC-LFM also proves to be an effective method to utilize the frequency outside the working band of the transducer in MAET.Significance. The method in this study compensates for the longitudinal resolution loss due to the uneven frequency responses. Combining with high-capability power amplifier and high-performance LNA, the MAET using FRC-LFM signal stimulation can potentially achieve high longitudinal resolution and high sensitivity, advancing MAET toward the clinical application.

Numerical simulation of multiphase flow and prediction of sediment wear in a large Pelton turbine

AbstractThe problem of sediment wear presents a significant challenge for hydraulic turbines operating in sediment‐rich rivers, particularly for high‐head Pelton turbines. In this study, the VOF model, SST k–ω model, and DPM model were employed to simulate the gas–liquid–solid three‐phase flow within a large Pelton turbine, which operates under a rated water head of 671 m and has a single capacity of 500 MW, at a hydropower station situated on a sediment‐laden river. The sediment wear prediction model, derived from the sediment wear test of the model turbine, was utilized to forecast the sediment wear on the flow components of the Pelton turbine at the hydropower station. The results show that there are obvious pressure and velocity gradients near the nozzle outlet of the Pelton turbine in the power station, and the wear of the nozzle surface is gradually increasing, and the wear in the downstream area of the nozzle is more serious. The wear rate at the needle tip surface reached 1.372 μm/h, while the socket ring surface exhibited a wear rate of 3.175 μm/h. he highest wear rate recorded for the water bucket is 0.940 μm/h. After a year of continuous operation, the maximum erosion observed was 5.62 mm on the runner bucket made of stainless steel and wear‐resistant metal, 8.23 mm on the spray needle, and 19.05 mm on the nozzle mouth ring, highlighting the severity of sediment wear on the Pelton turbine. It is recommended that surface treatment technology be applied to the flow‐through components of the Pelton turbine at this hydropower station to enhance the wear resistance of the turbine and extend the operational life of the unit.

Cost-effective reliability level in 100% renewables-based standalone microgrids considering investment and expected energy not served costs

Loss of load probability (LOLP) and expected energy not served (EENS) are commonly used in electrical power systems to evaluate reliability. LOLP defined as the probability that available generation capacity will be inadequate to supply customer demand. EENS defined as the expected amount of energy not being served to consumers by the system during the period considered due to system capacity shortages or unexpected power outages. Loss of Load Frequency (LOLF) is referred to a number of loss of load (LOL) event happened in the operation life span of the SMG. Loss of Load Reduction (LOLR) is defined as the required reduction in LOLF to obtain a specific reliability level. While power systems are designed to minimize LOLP and EENS, this is constrained by the total cost: investment cost, operation and maintenance cost, and cost of customer interruption (CCI). This research considers Standalone Microgrid (SMG), also known as Autonomous Microgrid which only operates in off-grid mode and cannot be connected to wider electrical power system. When designing a 100 % renewable energy integrated SMGs, it is crucial to determine the cost-effective reliability level (CERL). The CERL occurs when the total cost is minimum. This research proposes an approach to calculate the CERL for a fully renewable SMG. An analytical formulation is proposed to represent the LOLR needed to obtain a specific reliability level as a function of the required size of reliability improvement alternatives. The CCI is evaluated using LOLF and EENS indices. Finally, the total cost of the SMG system is evaluated for each reliability level. Consequently, the total cost of the SMG system is expressed as a function of reliability levels, and the minimum value of total cost and the corresponding reliability level are evaluated. In this research, a Monte Carlo Simulation (MCS) approach is used to find hourly LOLF, considering 25 years (219,000 h) of SMG lifespan, regression analysis is used for an analytical formulation, and mixed integer linear programming (MILP) is used for the investment decision making based on a cost minimisation approach. The result demonstrates that the CERL of the SMG system evaluated in the case study is 98.71 %.

Multi-energy harvesting: Integrating contact-mode and slide-mode triboelectric nanogenerators, and solar technologies for efficient power generation in small electronic

Harvesting energy from the environment is getting more attention daily to drive small electronics. This paper presents a hybrid energy harvesting module that uses contact-mode triboelectric nanogenerator, slide-mode nanogenerator, and solar energy to generate electrical power. The fabricated module has three parts, i.e., the base part operating in triboelectric contact mode, the rotary part employing lateral sliding triboelectricity, and solar cells for harnessing sunlight. The 3D designed module parts have been fabricated using 3D printer and laser cutting machine. Subsequently, the parts were assembled by applying triboelectric (Aluminum and Kapton) material onto them. The triboelectric contact mode generated 0.57 µW of electric power achieving power density achieved 57 µWm−2 at the contact area of 100 cm2. Electric power delivered by triboelectrification of the rotary part was 117 µW, whereas the power density was recorded as 232.6 µWm−2 at the contact area 503.36 cm2, and power delivered by solar cells was 66.64 mW. The designed module successfully delivered power to small electronic devices such as electronic thermometers, digital calculators, digital clocks, and 25 green-coloured LEDs. The implications of these findings suggest that such a hybrid module can significantly extend the operational life and independence of small-scale electronics, making it a promising solution for remote sensing, wearable technology, and IoT devices.

Optimum feature selection for classification of PD signals produced by multiple insulation defects in electric motors

Partial discharges (PD) are initiated in electrical equipment during various points of the equipment’s lifecycle. The intensity of PD defects rises continuously with time, which can lead to insulation degradation and reduced operational life of the electrical equipment. The optimum feature selection of PD signals captured, from different insulation defects, can enhance the classification accuracy of PD defects and facilitate better visualization of PD parameters for electric motor (EM) insulation monitoring and diagnostics. This paper presents a hybrid approach, based on Maximize Relevancy and Minimize Redundancy (mRMR) and random forest (RF), for the optimum feature selection and classification of PD signals in EMs containing multiple defects. For this purpose, four PD defects are developed in the EMs insulation under laboratory conditions, and 800 PD signals are acquired using a conventional IEC-60,270 experimental platform. The severity of these defects is determined and investigated based on PD characteristic parameters. Several features of both PD sweep signals and conventional PD pulses are extracted. Consequently, the mRMR feature selection technique is implemented to select the significant features of the detected PD signals. To establish the plausibility of this technique, several other feature selection algorithms, including RefliefF, Gini Index (GI), and Information Gain (IG), are introduced for the same datasets. The performance of all these feature selection algorithms is validated using three commonly used classification techniques such as RF, support vector machines (SVM), and k-nearest neighbors (k-NN). In summary, the results show that the combination of mRMR and RF proves to be the most effective feature selection algorithm for the classification of insulation defects in EMs, achieving an accuracy of 99.875%. This accuracy is significantly better than other feature selection and classification techniques and indicates its potential for application to other power system components.

Design of Gearings from Involute-Bevel Gears

The article presents formulas for determining the dimensions of involute-bevel gears and the gearings composed of them. It examines the most general cases of gearings formation, consisting of two involute-bevel gears with crossing axes (hyperboloid gearings), with intersecting axes (bevel gearings), and with parallel axes (cylindrical gearings). Gearings composed of involute-bevel gears have design, technological, and operational advantages compared to gearings composed of conventional cylindrical and bevel gears. The use of involute-bevel gearings with crossing axes allows for achieving the required contact character of the teeth from localized contact to linear contact, reducing sensitivity to manufacturing and assembly errors, and increasing the load capacity of the gearing compared to helical gearings from cylindrical gears. Bevel gearings with involute-bevel gears allow for the creation of gearings with any desired small shaft angles, which is difficult to achieve with conventional bevel gears. The use of internal meshing bevel gearings with modified tooth profiles in planetary reducers allows for gearings comparable to harmonic drives in terms of power and kinematic characteristics, but with a higher operational life. The use of involute-bevel gears in cylindrical gearings improves the smoothness of the mechanism and allows for adjusting the center distance and backlash in the meshing, making them suitable for backlash-free drives. By combining the taper angles of the gears and the inclination of the teeth, it is possible to create a one-way rotation mechanism - a freewheel mechanism. Modern CAD systems do not take into account the geometry features of gearings composed of involute-bevel gears, which limits their application in technology. The article proposes an algorithm for calculating the main geometric parameters of gearings composed of involute-bevel gears with arbitrary axis placement in space. Examples of geometric calculations of various types of gearings based on the proposed algorithm are provided.

Energy Harvesting Deadline Monotonic Approach for Real-time Energy Autonomous Systems

This paper presents an innovative scheduling algorithm designed specifically for real-time energy harvesting systems, with a primary focus on minimizing energy consumption and extending the battery's lifespan. The algorithm employs a fixed priority assignment which is the deadline monotonic policy, we have chosen it for its optimality and superior performance compared to other fixed priority scheduling methods. To achieve a balance between energy efficiency and system performance, we incorporated a DVFS (Dynamic Voltage and Frequency Scaling) technique into the algorithm. This adaptive approach enables precise control over the processor's operating frequency, effectively managing energy consumption while ensuring satisfactory system functionality. The core objective of our scheduling algorithm centers on optimizing energy utilization in real-time energy harvesting systems, specifically tailored to extend the battery's operational life. Rigorous evaluations, including comprehensive comparisons against established fixed priority scheduling algorithms, validate the algorithm's efficacy in significantly reducing energy consumption while preserving the system's overall functionality. By combining the deadline monotonic policy and DVFS technique, our proposed algorithm emerges as a promising solution for energy-autonomous systems, contributing to the advancement of sustainable energy practices in real-time applications. As energy harvesting technologies continue to progress, our algorithm holds valuable potential to provide critical insights for enhancing the efficiency and reliability of future energy harvesting systems.

Study on Oil Resistance of Polyurethane Protective Material

Abstract The polyurethane protective tape is a new type of protective material made by coating high performance pressure-sensitive adhesive on polyurethane elastomers, which is widely used in aviation. During its operational life, the polyurethane protective tape inevitably comes into contact with oil, and its oil resistance directly impacts its lifespan. This study focuses on the polyurethane protective tape and conducts immersion tests in No. 15 aviation hydraulic fluid, aircraft gear oil 4450 and RP3 aviation kerosene at room temperature. A comparative analysis was also conducted on the tensile strength, tear resistance, fracture morphology, chemical structure, and thermophysical properties before and after immersion. The research indicates that the tensile properties of polyurethane protective tapes remain essentially unchanged after immersion in RP3 aviation kerosene. After being immersed in No.15 aviation hydraulic fluid and aircraft gear oil 4450, the tensile strength of the polyurethane protective tape gradually decreases. Furthermore, compared to No.15 aviation hydraulic fluid, the rate of tensile strength reduction in polyurethane protective tape immersed in aircraft gear oil 4450 is more rapid. The resistance to tearing of polyurethane protective tapes diminishes gradually with prolonged immersion, with the rate of decline being greater for aircraft gear oil 4450 than for No.15 aviation hydraulic fluid, and even greater for RP3 aviation kerosene. The decrease in mechanical properties of polyurethane protective tapes after immersion in oil is attributed to the swelling effect of the oil, which reduces the intermolecular forces within the polyurethane material and leads to a decrease in physical cross-linking. This process is physical aging, with no evident chemical aging occurring.

Exploring the effect of Ti doping on the friction characteristic of DLC films on the surface of pump plunger in petroleum extraction environments

DLC film is considered to be one of the most promising film materials for improving the abrasion resistance and operation life of pump plungers draw upon its low friction and high hardness, but the friction characteristics and mechanism of the doping element Ti on pump plungers under the petroleum extraction environment are still unclear. In this paper, the friction performance and mechanism of the doping Ti for DLC film on the appearance of the pump plunger under the petroleum extraction environment were investigated at the microscopic scale by using the reactive molecular dynamics. The outcome shows that the Ti-DLC displays a reduction in average friction force of 78.82 % and a decrease in average temperature of 40.33 % in the oil extraction environment, thus improving the abrasion resistance of the pump plunger. Moreover, with the increase of Ti content, the friction will gradually decrease, and significantly low friction behavior can be even materialized without lubrication. It is found that the main reason for the low friction of Ti-DLC film is that the layered structure determined by Ti concentration is formed on the appearance of friction pair, which inhibits the formation of interfacial carbon bond and reduces the shear stress on the contact surface.

In situ microbubble-mediated strategy for highly efficient anti-crude oil-fouling membrane with parallel nanosheet structure

Membrane fouling caused by highly viscous oils severely hampers the long-term application of oil–water separation membranes. In situ aeration, achieved by applying a voltage to the membrane to produce bubbles, can effectively reduce the adhesion of oil contaminants. Herein, the parallel NiFe-layered double hydroxide arrays were successfully constructed on Ni foam using a hydrothermal method. Compared with NF@NFLDH having randomly aligned nanosheet arrays, NF@NFLDH-P can produce more numerous micro-size bubbles. A substantial number of the microbubbles spontaneously coalesced with oil droplets, and the synergy of buoyancy and kinetic energy significantly hindered oil fouling on the NF@NFLDH-P membrane. Specifically, this microbubble–mediated anti-oil-fouling strategy substantially reduced the flux attenuation and maintained a high flux recovery ratio during long-term crude oil–water separation, exhibiting a great operational life. This study suggests an innovative way to design future anti-fouling membranes with bubble-mediated capabilities.

A novel physics-based computational framework to model spacecraft solar array power under degradation: application to European Space Agency (ESA) Cluster mission

Accurate modeling and simulation (M&S) of spacecraft solar array power under degradation is essential for mission planning, remaining useful life assessment, and lifetime extension. A relevant example is ESA’s Cluster spacecraft fleet, launched in 2000 and operated at the European Space Operation Centre (ESOC), whose solar arrays have suffered severe degradation due to space radiation that has caused challenges to routine operations and mission planning. However, currently available physics-based and machine learning models have been proven ineffective in modeling the drastic reduction in power generation over the long operational life of the spacecraft.In response to these limitations, this work introduces a framework to model solar array degradation and predict power generation. It embeds a novel simplified physics-based model and a meta-heuristic optimization algorithm which exploits domain-specific knowledge and monitoring data for robust model parameter calibration and accurate power generation predictions. The results show the effectiveness of the proposed approach in avoiding overfitting and providing an accurate estimate of Cluster solar array power evolution.

Aerodynamic characteristics of wind turbines considering the inhomogeneity and periodic incentive of wake effects

In wind farms, the wake can lead to a loss of output power, and the uneven characteristics of wake can also exacerbate the fatigue load of downstream wind turbine (WT), affecting their operating life. To explore the impact of wake effects on downstream WT, this article proposes a new method for calculating the load of WT wake wind conditions and verifies it. Establishing a 3DJG wake model coupled with improved BEM for wind turbine aerodynamic performance calculation method. The influence of downstream WT operation phase angle and positions of 3D wake on the time-varying aerodynamic characteristics of downstream WTs was discussed from three perspectives: Blade elements on the spanwise, single blade and wind rotor. Results shown that: (1) For the blade element, calculated the shear force in the flapwise direction and the edgewise direction on each blade segment. The overall shear force of blade element in the vertical upward direction of WT blades is significantly greater than that in other directions. The non-uniformity of the wake is not sufficient to change the position of the maximum shear force on the blade. The position of the maximum shear force at each wake position is in the rear segments of the blade; (2) For the single blade, the most severe load fluctuation occurs when it is in the partial wake condition. The period of this fluctuation is 360°. When in full wake condition, the load fluctuation is relatively small, and due to the symmetry of the wake, the load fluctuation period is only 180°. The load standard deviation (SD) of the partial wake condition increases by 51 % compared to the full wake condition. (3) For the wind rotor, different wake positions have a weighty impact on the power loss of the WT rotor. Compared to the incoming shear wind, the power loss at the wake center can reach up to 54.22 %. At the wake boundary, the power loss of the WT is only 5.6 %. The non-uniformity of wake also has a periodic impact on the power output of the entire WT rotor, with the fluctuation period is 120°, and the fluctuation amplitude of no more than 2 %. This article provides a more intuitive quantitative analysis of the impact of wake on the time-varying aerodynamic characteristics of downstream WTs. It has certain reference value for the design strength verification of WTs, as well as the yaw strategy and layout design of wind farms.

Decay time estimate for LEO spacecraft

The growing concerns posed by orbital debris represent a serious threat to the future of space operations in low Earth orbit. With the goal of limiting the formation of new debris, space agencies are proposing international guidelines that satellites should be able to deorbiting within 25 years of the end of their operational life. Orbital decay is typically caused by atmospheric drag, so estimating the decay time of a satellite subject to drag is critical to assessing whether the guidelines are met. However, such estimate is a very challenging task because of the difficulty of accurately modeling atmospheric properties and because of the coupling of orbital dynamics with spacecraft attitude. In this paper, a simplified algorithm based on the King-Hele formulation is proposed to rapidly estimate the decay time of an orbiting satellite without imposing any assumptions on the spacecraft’s nominal size, mass, geometry or attitude. The algorithm accounts for the effect of solar activity level variations on atmospheric properties and drag coefficient through an iterative procedure and can be applied to any object in orbit. Numerical tests show that the predictions in terms of decay times are very accurate for satellites that are quite different in size and geometry, including the presence of an aerodynamic drag augmentation system such as a drag sail.

Machine Learning Prediction of Fuel Cell Remaining Life Enhanced by Variational Mode Decomposition and Improved Whale Optimization Algorithm

In predicting the remaining lifespan of Proton Exchange Membrane Fuel Cells (PEMFC), it is crucial to accurately capture the multi-scale variations in cell performance. This study employs Variational Mode Decomposition (VMD) to decompose performance data into intrinsic modes, elucidating critical multi-scale dynamics vital for understanding the complex degradation processes in fuel cells. In addition to VMD, this research utilizes an Improved Whale Optimization Algorithm (IWOA) to optimize a Back Propagation (BP) Neural Network. The IWOA focuses on precise adjustments of weights and biases, enabling the BP network to effectively interpret complex nonlinear relationships within the dataset. This optimization enhances the predictive model’s reliability and stability. Extensive experimental evaluations demonstrate that the integration of VMD, and the learning capabilities of the IWOA-optimized BP network significantly improves the model’s accuracy and stability across multiple predictions, thereby increasing the reliability of lifespan predictions for PEMFCs. This methodology offers a robust framework for extending the operational life and efficiency of fuel cells.

Task Scheduling Algorithm for Power Minimization in Low-Cost Disaster Monitoring System: A Heuristic Approach

This study investigates the optimization of a low-cost IoT-based weather station designed for disaster monitoring, focusing on minimizing power consumption. The system architecture includes application, middleware, communication, and sensor layers, with solar power as the primary energy source. A novel task scheduling algorithm was developed to reduce power usage by efficiently managing the sensing and data transmission periods. Experiments compared the energy consumption of polling and deep sleep techniques, revealing that deep sleep is more energy-efficient (4.73% at 15 s time intervals and 16.45% at 150 s time intervals). Current consumption was analyzed across different test scenarios, confirming that efficient task scheduling significantly reduces power consumption. The energy consumption models were developed to quantify power usage during the sensing and transmission phases. This study concludes that the proposed system, utilizing affordable hardware and solar power, is an effective and sustainable solution for disaster monitoring. Despite using non-low-power devices, the results demonstrate the importance of adaptive task scheduling in extending the operational life of IoT devices. Future work will focus on implementing dynamic scheduling and low-power routing algorithms to enhance system functionality in resource-constrained environments.